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Secondary analysis of existing data offers many advantages to the nurse researcher. Data from large-scale studies may be reanalyzed and refined by secondary analysts with a fresh perspective, thus enhancing the original study's contribution to scientific knowledge. High-quality data can be obtained for comparatively little expenditure of time and money. The secondary analyst, however, must exercise care in evaluating and analyzing a data set to maximize the internal and external validity of the reanalysis. Because the secondary analyst's lack of involvement in data collection procedures may decrease insight into the original study's limitations, vigilant skepticism should accompany all phases of the research process in secondary data analysis, just as it should in all other research. Miller (1982) advised, "Begin by assuming the worst and seek out the same kinds of information about sample selection procedures, sample size, response rates, field procedures, and coding conventions that you would insist on if you were collecting your own data" (p. 722). By systematically evaluating potential data sets according to rigorous predetermined criteria, the nurse researcher can minimize the possible pitfalls inherent in secondary analysis. On the other hand, investigators who use secondary sources appropriately can make significant contributions to nursing science at less cost than that engendered by traditional research methods.
Jacobson et al. (Sun,) studied this question.